Most AI conversations in pharma start with generation: drafting, summarizing, chatting.
Many decisions in a safety or medical information workflow are smaller than that:
- Is this a possible adverse event?
- Which special situation applies?
- How urgent is this message?
Those are narrow questions with fixed answers. System 1 models are built for exactly that. You send the text plus your questions. You get back a yes or no, a pick from your list, or a score, each with a probability, all in one call.
Kahneman called this fast thinking. We made a one-minute explainer on it.
In Small Doses, Ch 1: Thinking fast and slow, for AI
Check out this cool work from our team! You can now easily generate consistent and explorable 3D worlds - super happy to have contributed to it :)
Excited to see all the cool 3D world generations from this model!
Today, we released Lyra 2.0, a framework for generating persistent, explorable 3D worlds at scale, from NVIDIA Research.
Generating large-scale, complex environments is difficult for AI models. Current models often “forget” what spaces look like and lose track of movement over time, causing objects to shift, blur, or appear inconsistent. This prevents them from creating the reliable 3D environments required for downstream simulations. Lyra 2.0 solves these issues by:
✅ Maintaining per-frame 3D geometry to retrieve past frames and establish spatial correspondences
✅ Using self-augmented training to correct its own temporal drifting.
Lyra 2.0 turns an image into a 3D world you can walk through, look back, and drop a robot into for real-time rendering, simulation, and immersive applications.
➡️ Learn more: https://t.co/ROR7miJeCU
📄 Read the paper: https://t.co/1osU9EGjGD
Seeing how realistic video generation has become, I always imagined a model that continuously constructs a 3D world as you move through previously unseen environments. Today, I’m excited that we’ve made it real!
Lyra 2 turns images into explorable 3D worlds—and the environment generated along your trajectory can be exported as 3D Gaussian Splatting and meshes, making it directly usable for real-time rendering and physics simulations.
Our team at NVIDIA is recruiting PhD research interns for the upcoming summer! Apply now! 🥳 Feel free to contact me for any questions or if you’re interested in getting to know the team!
Listings are here:
https://t.co/Lp5jJYvorD
https://t.co/XJR8PE5jzT
If you work with pytorch and you haven't read this blog, you are missing out big time.
Insane detailing. Even @karpathy recommended reading this in his videos.